Evidence map›Paper›PMID 41144205›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Evolutionary Genomic Analyses of Cryptosporidium.

Tianpeng Wang, Lihua Xiao

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Tianpeng WangState Key Laboratory for Animal Disease Control and Prevention, Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Lihua XiaoState Key Laboratory for Animal Disease Control and Prevention, Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing amount of whole-genome sequencing (WGS) data allows us to study the evolution and transmission of Cryptosporidium spp. at the population level. Population genomics is helping us to understand the genetic structure and adaptive evolution of Cryptosporidium and the mechanism and determinants of emergence of hypertransmissible subtypes and variants. The integrated pipeline described here provides an example of the use of WGS data for evolutionary genomic analysis of Cryptosporidium.

Indexed as

CryptosporidiumEvolution, MolecularGenome, ProtozoanGenomicsAnimalsCryptosporidiosisHumansPhylogenyWhole Genome SequencingAdaptationEvolutionPopulation genomicsPopulation structureRecombination

Identifiers

PMID41144205

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.